基于UKF的AUV多尺度容错对接导航算法研究  

UKF Based Multiscale Fault Tolerant Docking Navigation Algorithm for AUVs

作　　者：夏楠 曾庆军[1] 孙啸天 许赫威 任申真 XIA Nan;ZENG Qingjun;SUN Xiaotian;XU Hewei;REN Shenzhen(School of Computer Science,Jiangsu University of Science and Technology,Zhenjiang 212000,China;T-SEA Marine Technology Co.Ltd.,Suzhou 215000,China)

机构地区：[1]江苏科技大学电子信息学院,江苏镇江212000 [2]中科探海(苏州)海洋科技有限责任公司,江苏苏州215000

出　　处：《电光与控制》2023年第3期116-121,共6页Electronics Optics & Control

基　　金：国家自然科学基金(11574120);江苏省产业前瞻与共性技术项目(BE2018103);江苏省研究生实践创新计划(SJCX21_1744)。

摘　　要：针对回收对接过程中,自主式水下机器人(AUV)的组合导航系统由于子传感器量测信息发生阶跃性突变而导致导航系统滤波发散的问题,以分布式联邦滤波结构为基础,提出了一种基于无迹卡尔曼滤波(UKF)的自适应容错异步融合算法。该算法以传感器的采样率为依据,建立分布式组合导航多尺度系统模型,在辅助信息突变时利用自适应渐消因子优化UKF动态调整增益矩阵、削弱故障信息对滤波精度的影响,使得多源导航系统更加稳定、容错性更高。仿真实验表明,提出的自适应容错UKF异步融合算法能更好地抑制滤波发散,提升导航系统的精度与可靠性,有效提高AUV的导航系统在回收对接过程中的稳定性与容错性。In order to solve the problem that the navigation system filter diverges due to the step mutation of sub-sensor measurement information in the integrated navigation system of AUV during the recovery and docking process,on the basis of unscented Kalman filter,an adaptive fault-tolerant asynchronous fusion algorithm is proposed based on the distributed federated filter structure.According to the sampling rate of the sensor,the algorithm establishes a distributed integrated navigation multi-scale system model.When the auxiliary information changes suddenly,the adaptive extinction factor is used to optimize the UKF,and the gain matrix is dynamically adjusted to weaken the influence of fault information on filtering accuracy,which makes the multi-source navigation system more stable and fault-tolerant.Simulation experiment shows that the proposed adaptive fault-tolerant UKF asynchronous fusion algorithm can better suppress the filter divergence and improve the accuracy and reliability of the navigation system, and improve the stability and fault tolerance of the navigation system in the process of recovery and docking.

关 键 词：自主水下机器人 回收对接 联邦滤波 异步融合 容错滤波 UKF 组合导航 

分 类 号：U666.11[交通运输工程—船舶及航道工程]